Show HN: Train CIFAR10 to 94% in under 10 seconds on a single A100 Hi, My career is currently in this field, and I created this project as (effectively, among other things) a living resume, and to also be a really great workbench for hacking/experimenting on different methods. Testing and getting a feel for how different methods work within this framework is truly a delight, and quite simple/fast. Additionally, generally speaking, many of the mathematical concepts should transfer, so this (for me) has been a really great proving grounds in testing out how something might work in a different place in the real world. We hope to get under 2 seconds of training time (for 94%) within about two years or so, so stay tuned for updates as we continue to push more changes that take us faster and faster than our starting point of ~18.1 seconds or so. By the way, this architecture and training hyperparameters do indeed scale well, just increase epochs from 10->80 and base_depth from 64->128 and you'll have about 95.77% accuracy in about 188 seconds or so (just over 3 minutes :D). That alone is a huge boon! Great to see scaling laws working well within this very, very tight hyperparameter resolution. Feel free to let me know if you have any questions, Hacker News always seems to get me the most traffic. I really love talking about this project, and can't really seem to find anyone to nerd out about it with. This is very, very cool stuff! So feel free to leave a comment, and I'd love to jump in and chat about it! :D :) <3 <3 :)))) https://github.com/tysam-code/hlb-CIFAR10 January 30, 2023 at 07:58AM
Show HN: Launch VM workloads securely and instantaneously, without VMs Hello HN! We've been working on a new hypervisor https://kwarantine.xyz that can run strongly isolated containers. This is still a WIP, but we wanted to give the community an idea about our approach, its benefits, and various use cases it unlocks. Today, VMs are used to host containers, and make up for the lack of strong security as well as kernel isolation in containers. This work adds this missing security piece in containers. We plan on launching a free private beta soon. Meanwhile, we'd deeply appreciate any feedback, and happy to answer any questions here or on our slack channel. Thanks! April 29, 2021 at 07:50AM
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